Population mobility models of urban disease outbreak

城市疾病爆发的人口流动模型

• 批准号: 7230432
• 负责人: STEPHEN G EUBANK
• 金额: $ 67.13万
• 依托单位: VIRGINIA POLYTECHNIC INST AND ST UNIV
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-05-01 至 2009-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7230432
• 关键词: Accident and Emergency department; Address; Adult; Aerosols; Algorithms; Behavior; Caregivers; Child; Computer software; Computing Methodologies; Critical Pathways; Data; Databases; Detection; Disease; Disease Outbreaks; Disease model; Effectiveness; Elements; Ensure; Epidemic; Epidemiology; Exposure to; Goals; Health; Health Care Seeking Behavior; Health Personnel; Heart; Home environment; Human; Immune response; Individual; Informatics; Intervention; Location; Medicine; Modeling; Pathway interactions; Pattern; Population; Population Sizes; Property; Quarantine; Reaction; Research; Resources; Role; Schedule; Simulate; Social Network; Specific qualifier value; Standards of Weights and Measures; Symptoms; System; Time; TimeLine; Translating; Urban Population; Vaccination; Vector-transmitted infectious disease; Visit; Work; base; design; desire; disease transmission; improved; novel; pathogen; response; simulation; tool; transmission process; urban area

DESCRIPTION (provided by applicant): This project will design, build, and validate models of disease epidemiology and response systems based on individuals' roles in a social network. It will focus on mathematical and computational methods for modelling exposure to pathogens and their products as well as the effectiveness and consequences of different intervention strategies. In particular, it will explore the effects of human contact patterns in urban areas on disease transmission dynamics and the consequences of proposed early and mid-term responses to intentional or natural releases of pathogens. The project will produce a simulation system tracking the transmission of multiple co-circulating and interacting diseases in a synthetic population. Flexible user-specified scenarios will include such parameterized elements as: host-pathogen interactions; disease transmission dynamics; initial health state of the population; the mode of a pathogen's introduction into the population; and choice and scheduling of response strategies, which might be demographically and/or geographically targeted. The simulation will rely on existing estimates of contact patterns in a synthetic urban population of 1.5 million individuals. Research topics will include how these patterns might change in the presence of an outbreak. In addition, the project will undertake a mathematical, structural analysis of the estimated contact patterns at the heart of the simulation. The goals of this analysis are: to determine the features of social networks that best characterize their response to epidemics and mitigation strategies; to develop efficient algorithms for evaluating these features in very large networks; to estimate variability in these features among different urban areas and different size populations; and to provide the capability for generating stochastic but realistic instances of social networks. All results will be communicated in a timely fashion to the MIDAS Informatics Group. The project intends to provide software (both the simulation itself and analysis tools for social networks) and also epidemiological data arising from simulation of a set of standard scenarios

描述（由申请人提供）：该项目将根据个人在社交网络中的角色设计，建立和验证疾病流行病学和反应系统的模型。 它将重点介绍用于建模病原体及其产品的数学和计算方法，以及不同干预策略的有效性和后果。 特别是，它将探讨人类接触模式在城市地区对疾病传播动态的影响，以及拟议的早期和中期对病原体有意或自然释放的反应的影响。 该项目将产生一个模拟系统，该系统跟踪合成人群中多重循环和相互作用疾病的传播。 灵活的用户指定的方案将包括以下参数化元素：宿主 - 病原体相互作用；疾病传播动力学；人口的最初健康状况；病原体引入人群的模式；以及响应策略的选择和调度，这些响应策略可能是人口统计学和/或地理位置针对的。 模拟将依靠150万个人的合成城市人口中的接触方式估计值。 研究主题将包括在爆发存在下这些模式如何改变。 此外，该项目将对模拟核心的估计接触模式进行数学，结构分析。 该分析的目标是：确定社交网络的特征，这些特征最能表征其对流行病和缓解策略的反应；开发有效的算法来评估非常大的网络中的这些功能；估计不同城市地区和不同规模人群之间这些特征的可变性；并提供产生随机但现实的社交网络实例的能力。 所有结果将及时传达给MIDAS信息学组。 该项目旨在提供软件（仿真本身和社交网络的分析工具），以及由一组标准方案的模拟引起的流行病学数据